Status Dx de la Base UIID

Llamando librerías

library(ggplot2)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

Leemos datos y agregamos Interpretación de Estatus

base<-read.csv("../data/UIID_statusdx.csv",header=T)
class(base)

## [1] "data.frame"

base<-base%>%
  as_data_frame()%>%
  mutate(EstatusDx=as.character(ESTATUDX),
         EstatusDx=if_else(ESTATUDX==0,"C. Sin IDP",EstatusDx),
         EstatusDx=if_else(ESTATUDX==1,"B. Con IDP",EstatusDx),
         EstatusDx=if_else(ESTATUDX==2,"A. IDP en estudio",EstatusDx))
class(base)

## [1] "tbl_df"     "tbl"        "data.frame"

base

gg01<-ggplot(data=base,aes(x=aniocons, fill=EstatusDx)) + 
    geom_density(adjust=1.5, position="fill")
# gg01

gg01_pl<-ggplotly(gg01)

## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`

gg01_pl$x$layout$xaxis$title<-"Año de consulta"
gg01_pl$x$layout$yaxis$title<-"densidad"
gg01_pl

• El porcentaje de pacientes diagnosticados con IDP se mantiene constate o estable alrededor del 30%.

• Se observa que antes (2011) había una mayor proporción de casos en los que se descartaba IDP y, que hoy, parte de esa propoción de casos (~30%), pasó a ser IDP en estudio, mostrando ser hoy más minuciosos para confirmar o descartar el diagnóstico.

Agrupando por año

gb01<-base%>%
  group_by(aniocons)%>%
  summarise(n_px=n(),
            per_px=round(n_px/nrow(.),4))
gb01

gb02<-base%>%
  group_by(aniocons)%>%
  mutate(n_px=n()#,
         # per_px=round(n_px/nrow(.),4)
         )%>%
  ungroup()%>%
  group_by(aniocons,ESTATUDX)%>%
  mutate(n_st_anio=n(),
         per_st_anio=round(n_st_anio/n_px,4))%>%
  filter(row_number()==1)%>%
  select(-Expediente)

gb02

gg02 <-ggplot(gb02, aes(aniocons, n_st_anio))+
  geom_bar(stat = "identity", aes(fill = EstatusDx))

# gg02 

gg02_pl<-ggplotly(gg01)

## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`

gg02_pl$x$layout$xaxis$title<-"Año de consulta"
gg02_pl$x$layout$yaxis$title<-"Frecuencia de casos"
gg02_pl